The invention discloses a compiling optimization method and device for a machine learning model. The method comprises the steps of operating a first machine learning model to process N data sets, andN sets of model operation information are obtained; determining N operation sets in the first group of operations according to the N groups of model operation information; determining a plurality of operation subsets allowed to be compiled respectively in the first group of operations according to the N operation sets; and using the target compiler to compile the operation subset corresponding toeach compiling area. According to the method and the device, the technical problems of long compiling period and resource waste caused by the fact that sampling information during operation is not introduced during compiling of machine learning are solved.